Intersection of the DEA result

There are more differentially expressed transcripts detected between the Treated / Untreated conditions using the Paired-end protocol. This seems logical as the data from the paired-end protocol are more homogeneous as shown on the kalisto output concerning the percentage of aligned reads.

What’s more, when the treated protocol is used for PCA, 97% of the treated/non-treated variability is explained, compared with 89% for the single-end protocol. The biological variability that interests us most is much more concentrated than when the single-end protocol is used. As the treatment effect is much more highlighted in the Paried-end protocol, the DEA results will be much more interesting to exploit. The clarity and uniformity of the variability explained by the treatment condition in the paired-end condition may also explain why we obtain a greater number of differentially expressed transcripts compared with the single-end protocol.

The single-end protocol shows that there is more noise in the overall results and is therefore less interesting to use for this type of analysis.

In conclusion, there is a very clear effect of treatment on the individuals sequenced here, whatever the protocol used. It’s just that this effect looks much better highlighted in the data when the paired-end protocol is used.

Multivariate model (EXPERIMENTAL)